Subplotting after groupby with pandas plot

Question

I have a dataframe like so:

df = pd.DataFrame({"idx":[1,2,3]*2,"a":[1]*3+[2]*3,'b':[3]*3+[4]*3,'grp':[4]*3+[5]*3})
df = df.set_index("idx")
df
     a  b  grp
idx           
1    1  3    4
2    1  3    4
3    1  3    4
1    2  4    5
2    2  4    5
3    2  4    5

and I would like to plot the values of a and b as function of idx. Making one subplot per column and one line per group.

I manage to do this creating axis separately and iterating over groups as proposed here. But I would like to use the subplots parameter of the plot function to avoid looping. I tried solutions like

df.groupby("grp").plot(subplots=True)

But it plot the groups in different subplots and removing the groupby does not make appear the two separated lines as in the example.

Is it possible? Also is it better to iterate and use matplotlib plot or use pandas plot function?

Scott Boston · Accepted Answer · 2020-11-25 18:35:14Z

1

IIUC, you can do something like this:

axs = df.set_index('grp', append=True)\
  .stack()\
  .unstack('grp')\
  .rename_axis(['idx','title'])\
  .reset_index('title').groupby('title').plot()

[v.set_title(f'{i}') for i, v in axs.items()]

Output:

Maybe eaiser to simple loop and plot:

fig, ax = plt.subplots(1,2, figsize=(10,5))
ax = iter(ax)
for n, g in df.set_index('grp', append=True)\
              .stack()\
              .unstack('grp')\
              .rename_axis(['idx','title'])\
              .reset_index('title').groupby('title'):
    g.plot(ax=next(ax), title=f'{n}')

Output:

edited Nov 25, 2020 at 18:35

answered Nov 25, 2020 at 15:57

Scott Boston

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2 Comments

Heko Over a year ago

Almost there but the code you proposed generates the two plots separately and I would like to have them as subplots of the same figure

Scott Boston Over a year ago

@Heko I think it is probably simplier to loop and plot.

vegiv · Accepted Answer · 2020-11-25 14:31:29Z

-1

If i understod your question correct, you can access columns and rows in a pandas dataframe. An example can be like this:

import numpy as np
import matplotlib.pyplot as plt
x = np.array(df['idx']) 

a = np.array(df['a']) 

b = np.array(df['b']) 

plt.subplot(1,2,1)#(121) will also work
#fill inn title etc for the first plot under here
plt.plot(x,a)
plt.subplot(1,2,2)
#fill inn title etc for the second plot under here
plt.plot(x,b)
plt.show()

edit: Sorry now changed for subplot.

edited Nov 25, 2020 at 14:31

answered Nov 25, 2020 at 14:20

vegiv

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5 Comments

Bhbf Over a year ago

The i in import should be Lower Case

Heko Over a year ago

Thank you the question was unclear, I edited it. And hope you will understand what I want with the subplots. As mentioned I would like to use the subplots parameter of the plot function and not looping over the columns.

Bhbf Over a year ago

plt.plot(x,a), x should be Upper case

vegiv Over a year ago

@EzzaldeenAlribi i changed it now, was typing on the phone, and didnt bother with it as it was only ment to guide to an answer.

vegiv Over a year ago

@Heko Still not quite sure how you want to do it, but pandas plot function is just matplotlib plot under. "The plot method on Series and DataFrame is just a simple wrapper around plt.plot()"-from docs.

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